MR. BAKER: Let’s start with the news today about a new deal for Watson, your cognitive-computing element. It’s a deal with GM to introduce the Watson technology into OnStar. Can you explain how it works and how this is going to change the driving experience for us?
MS. ROMETTY: It’s very customized and tailored, and learns from how you behave and what you do. Everything from reminding you to pick up your child’s prescription on the way home, to it knows your coffee, it orders it for you, and it gets smarter and smarter from all these interactions. This will roll out with 2017 cars.
MR. BAKER: Watson has all kinds of applications. This OnStar deal puts it more directly into the consumers’ hands. Have you got more plans to bring it to the consumer?
MS. ROMETTY: I expect that to be happening through lots of clients. Watson is available as a platform. Anybody could build on it. And there are dozens of things available.
It touches consumers. It’s Medtronic with diabetes products that will be rolling out now, predicting hypoglycemia. That kind of thing.
There was maybe an interesting one just today. We had done some work with a record producer, Alex Da Kid. He does Rihanna, Imagine Dragons, some names that you would know. He just produced a new record with Watson helping him. Watson analyzed, I guess you could call it the world’s diary. It was the last five years of everything, tweets, what was said, to get a feeling of how people felt. Then did something called Watson Beat [that finds] what is it that makes people react emotionally to different music tones. And then another whole thing around, look at the lyrics of all the top songs in the Billboard 100 for as long as we could go, and what makes them hits?
So he did this collaboration, which is a big point of cognitive, it’s man and machine together. This song has popped. And so he’s going to do a couple more. It’s this idea, augmented intelligence. Not artificial intelligence.
MR. BAKER: This is somewhere where IBM’s been through successive changes. You’re in the process of another one. Right now, I think cognitive computing and cloud computing are about 40% of your revenue. Fifty percent, I think analysts say, by the end of next year. Have you gone at a fast enough pace?
MS. ROMETTY: A lot of tech companies come and go. And they can transform through one era, through two. It is something very different to go three, four and five different eras. And I’ve always said, and I say to our teams, and it’s even true with Watson, I say, “You can’t define yourself by a product.” It’s why we’ve been able to be 105 years old. We do define ourselves as working on the most challenging business and societal problems.
But the how you do it does change. So the how of this era has a lot to do, and it will make you able to solve really difficult, unsolvable problems.
Cloud will make this ubiquitous. Then with what we call cognitive, you will really get at all this data that is otherwise unharnessable. And you will solve stuff. We’re seeing it happen with health care, things that cannot be solved. There are a lot of things we do to run core franchises of the world. I keep repeating, remember, we run 80% of the airline operations that are out there. We run almost all the major banks of the world. Those are not high-growth businesses, but those are important businesses that we’ll do, and bring this to it.
MR. BAKER: Let’s talk about some of the issues around AI, or cognitive computing. There are a lot of concerns raised about ethics, and what does it mean when machines are potentially more intelligent, ultimately, than humans.
MS. ROMETTY: I would back up and make a couple points about it. First, people often talk about the fear about jobs around this topic. All the way to the other end of the spectrum, machines with a mind of their own and what could happen.
On the job front, this is a serious topic, but it is broader. Every era of technology has had an impact on jobs. Whatever this era will be called, it puts a premium on education, and not just higher education. With less education you still have to have math and technical skills to be able to live in this world. There are many things we can do about it.
Now, go to the other side [and the danger of superintelligent machines]. Most of what that comes from is when people talk about unsupervised learning, which has not yet been solved.
Watson is trained. It is supervised learning. If you gave these systems data and just said, “Be a doctor,” it wouldn’t be possible. They have to be trained.